Predicting the Pathologic Complete Response After Neoadjuvant Pembrolizumab in Muscle-Invasive Bladder Cancer. (9th June 2020)

• Record Type: Journal Article
• Authors: Bandini, Marco; Ross, Jeffrey S; Raggi, Daniele; Gallina, Andrea; Colecchia, Maurizio; Lucianò, Roberta; Giannatempo, Patrizia; Farè, Elena; Pederzoli, Filippo; Bianchi, Marco; Colombo, Renzo; Gandaglia, Giorgio; Fossati, Nicola; Marandino, Laura; Capitanio, Umberto; Deho', Federico; Ali, Siraj M; Madison, Russell; Chung, Jon H; Salonia, Andrea; Briganti, Alberto; Montorsi, Francesco; Necchi, Andrea
• Is Part Of: Journal of the National Cancer Institute. Volume 113:Number 1(2021)
• Page Start: 48
• Page End: 53
• Publication Date: 2020-06-09
• Subjects: Cancer -- Periodicals; Cancer -- Research -- Periodicals; 616.994
• DOI: 10.1093/jnci/djaa076
• Languages: English
• ISSNs: 0027-8874

Abstract

Abstract: Background: In the PURE-01 study (NCT02736266), we aimed to evaluate the ability to predict the pathologic complete response (pT0N0) after pembrolizumab by using clinical and tumor biomarkers. Methods: In an open-label, single-arm, phase 2 study, 3 courses of 200 mg pembrolizumab preceding radical cystectomy were administered in patients with T2-4aN0M0 muscle-invasive bladder cancer. The analyses included a comprehensive genomic profiling and programmed cell-death-ligand-1 (PD-L1)–combined positive score assessment (CPS; Dako 22C3 antibody) of pre- and posttherapy samples. Multivariable logistic regression analyses evaluated baseline clinical T stage and tumor biomarkers in association with pT0N0 response. Corresponding coefficients were used to develop a calculator of pT0N0 response based on the tumor mutational burden (TMB), CPS, and the clinical T stage. Decision-curve analysis was also performed. All statistical tests were 2-sided. Results: From February 2017 to June 2019, 112 patients with biomarker data were enrolled (105 with complete TMB and CPS data). Increasing TMB and CPS values featured a linear association with logistic pT0N0 probabilities ( P = .02 and P = .004, respectively). For low TMB values (≤11 mut/Mb, median value, n = 53), pT0N0 probability was not associated with increasing CPS. Conversely, for high TMB values (>11 mut/Mb, n = 52), pT0N0 was statistically significantly associated with higher CPS ( P = .004). The C index of the pT0N0 probability calculator was 0.77. On decision-curve analysis, the net benefit of the model was higher than the "treat-all" option within the clinically meaningful threshold probabilities of 40%-50%. Conclusions: The study presents a composite biomarker-based pT0N0 probability calculator that reveals the complex interplay between TMB and CPS, added to the clinical T stage.